BUS 120 · AI for Project Managers

Led by Druckerian Management Simulacrum

A practical short course on integrating generative AI tools into project management across Agile, hybrid and traditional settings.

1. Module 1

   AI and the Project Manager

   Led by Druckerian Management Simulacrum

   The question

   What is generative AI actually doing when it produces text, and where in a project manager's daily work does that capability create genuine value — as opposed to the mere appearance of productivity?

   Outcome

   The student can articulate what generative AI is (and is not) and has mapped their own PM tasks against AI augmentation potential.

   Sub-units

   1. ○ 1.1 What Generative AI Actually Is Open this unit → ✓ ↻
   2. ○ 1.2 Where AI Fits in Your Practice Open this unit → ✓ ↻
   Begin the course → Print certificate of completion
2. Module 2

   Planning and Scheduling with AI

   Led by Druckerian Management Simulacrum

   The question

   AI can generate a Work Breakdown Structure in seconds. But a plan produced without thinking is a plan without understanding. How do you use AI to accelerate planning while preserving the judgement that makes a plan useful?

   Outcome

   The student can draft, refine and critically evaluate an AI-generated project plan, correcting gaps and estimates based on organisational knowledge. (Practical)

   Sub-units

   1. ○ 2.1 Building a Work Breakdown Structure with AI Open this unit → ✓ ↻
   2. ○ 2.2 Scheduling, Dependencies and Estimation Open this unit → ✓ ↻
   3. ○ 2.3 Prompt Engineering for Planning Open this unit → ✓ ↻
   Open this module → Print certificate of completion
3. Module 3

   Communication and Documentation

   Led by Druckerian Management Simulacrum

   The question

   Project managers spend most of their time communicating. AI excels at drafting reports, emails and briefs — but when does AI-generated communication help, and when does it undermine the trust it is supposed to build?

   Outcome

   The student can produce audience-appropriate project communications with AI assistance and can identify scenarios where AI-generated communication is inappropriate. (Practical)

   Sub-units

   1. ○ 3.1 Status Reports and Stakeholder Briefs Open this unit → ✓ ↻
   2. ○ 3.2 Adapting Communication for Audiences Open this unit → ✓ ↻
   3. ○ 3.3 The Limits of AI Communication Open this unit → ✓ ↻
   Open this module → Print certificate of completion
4. Module 4

   Risk, Quality and Decision Support

   Led by Druckerian Management Simulacrum

   The question

   A well-formatted risk register can create an illusion of rigour. How do you use AI to strengthen risk analysis without mistaking pattern-based output for genuine organisational insight?

   Outcome

   The student can generate, evaluate and improve an AI-assisted risk register and can structure a decision matrix that goes beyond the AI's initial analysis. (Analytical)

   Sub-units

   1. ○ 4.1 Building a Risk Register with AI Open this unit → ✓ ↻
   2. ○ 4.2 Scenario Modelling and Decision Support Open this unit → ✓ ↻
   Open this module → Print certificate of completion
5. Module 5

   Ethics, Limitations and Team Adoption

   Led by Druckerian Management Simulacrum

   The question

   You now know what AI can do for your projects. But what should it do? What data can you safely share with AI tools? How do you introduce AI to a team without undermining trust — or your own skills?

   Outcome

   The student has a written personal policy for AI use in project management and can plan the responsible adoption of AI tools within a project team. (Professional Practice)

   Sub-units

   1. ○ 5.1 Privacy, Policy and Accountability Open this unit → ✓ ↻
   2. ○ 5.2 Introducing AI to Your Team Open this unit → ✓ ↻
   3. ○ 5.3 Your Personal AI Policy Open this unit → ✓ ↻
   Open this module → Print certificate of completion